A latent profile analysis of prenatal depression and anxiety in Chinese women with twin pregnancies

A latent profile analysis of prenatal depression and anxiety in Chinese women with twin pregnancies | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A latent profile analysis of prenatal depression and anxiety in Chinese women with twin pregnancies Dongsun Chen, Bing Lun, Hongxia Cui, Mingchen Fu, Liu Yang, Dongqi Yang, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8951651/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background While previous studies have investigated the prevalence and associated factors of prenatal depression and anxiety among women with twin pregnancies, most of these studies have overlooked the substantial variation in symptoms presentation. This study aimed to use latent profile analysis to identify the subgroups and associated factors of prenatal depression and anxiety among women with twin pregnancies. Method A cross-sectional study was conducted from October 2024 to October 2025, and a total of 334 women with twin pregnancies were included using convenience sampling. Participants were surveyed using a self-design socio-demographic information, Edinburgh Postnatal Depression Scale, Generalized Anxiety Disorder-7, Perceived Social Support Scale, and Simplified Coping Style Questionnaire. Latent profile analysis was performed to identify prenatal depression and anxiety subgroups among women with twin pregnancies, univariate analysis and multiple logistic regression were used to analyze the related factors. Result LPA identified two profiles of prenatal depression and anxiety: “low-risk group” (65.0%) and “high-risk group” (35.0%). Multivariate logistic regression revealed that lack of medical insurance, pregnancy-related complications, low family support, negative coping styles, and absence of positive coping styles significantly influenced high-risk group (all P < 0.05). Conclusion Two subgroups of prenatal depression and anxiety were identified among women with twin pregnancies. In the future, it would be more meaningful for obstetric primary health institutions to establish stratified management system and standardized interventions based on different subgroups. twin pregnancies depression anxiety latent profile associated factors Figures Figure 1 1 Introduction Pregnancy represents a significant life event for women, and maternal mental health has been globally acknowledged as a critical priority in public health[ 1 ]. During pregnancy, women are particularly vulnerable to suffer from mental health problems due to significant physical, emotional, and psychological changes, with a prevalence of over 10% in developed countries and over 25% in developing countries[ 2 ], among which depression and anxiety are the most common mental health issues[ 3 ]. A global meta-analysis investigating the prevalence of mental health issues during pregnancy revealed that the rates of depressive and anxiety symptoms among pregnant women were 27% and 37% respectively[ 4 ]. In China, a study involving 1349 pregnant women demonstrated that the proportions of those experiencing prenatal depressive symptoms reached 19.2%, with anxiety symptoms showing a slightly higher prevalence at 23.7%[ 5 ]. Numerous studies have confirmed that prenatal depression and anxiety have been linked to increasing risk of maternal complications and poor birth outcomes, as well as an increased risk of cognitive and behavioral development in the offspring[ 6 , 7 ]. Furthermore, depression and anxiety during pregnancy is also associated with an increased incidence of postpartum psychological disorders, even lead to suicidal behaviors or infanticide in severe cases[ 8 , 9 ]. In recent years, with the widespread application of assisted reproductive technology and the growing number of advanced maternal age pregnancies, the incidence of twin pregnancy has increased remarkably[ 10 , 11 ]. Evidence has shown that the incidence of twin pregnancies has increased by 50% over the last fifty years[ 12 , 13 ].Specifically, twin pregnancy occurs 1%~2.5% in some developed countries (e.g., America, Poland) [ 14 , 15 ]and 0.6%~3% in some developing countries[ 16 , 17 ] (e.g., Asia, Africa). In China, the latest national survey involving 5686 hospitals reported that twin pregnancy accounted for approximately 1.41% of all pregnancies[ 18 ]. As a high-risk obstetric condition, twin pregnancy is associated with both increased risk of maternal and neonatal complications[ 19 , 20 ]. Additionally, compared to those with singleton pregnancies, women with twin pregnancies faced with physiological adaptations, doubled economic burdens and caregiving responsibilities, these all leading to a greater higher prevalence of prenatal depression and anxiety[ 21 , 22 ]. Previous studies have shown that approximately 34.8% of women with twin pregnancies suffered from prenatal depressive symptoms and 37.1% experienced anxiety symptoms, significantly higher than women with singleton pregnancies[ 18 ]. Therefore, prenatal anxiety and depression among women with twin pregnancies have emerged as urgent public health concerns. Previous research on prenatal depression and anxiety mainly focus on women of singleton pregnancies, women with twin pregnancies have rarely been investigated. Existing a few researches have investigated the level of prenatal depression and anxiety among women with twin pregnancies in different regions, and analyzed the relationship between prenatal depression and anxiety and other factors[ 23 – 25 ]. However, these studies defined the level of prenatal depression and anxiety of women with twin pregnancies only based on the total score of the scale or scale boundary values[ 23 – 25 ], ignored the significant substantial variation in symptoms presentation among heterogeneous groups of individuals. Previous studies have proven that even individuals present similar levels of anxiety or depression, there still exists differences among individuals regarding to symptom patterns and outcomes[ 26 , 27 ]. This variable-centered classification not only causes the results of these studies couldn’t truly reflect the symptoms of depression and anxiety among women pregnant with twins, but also makes it difficult to develop precise interventions with different risk characteristics and affects the effectiveness of interventions. As an “individual-centered” approach, latent profile analysis (LPA) is well-suited to focus on the group heterogeneity and categorize subgroups with shared characteristics according to the response patterns, and analyzed the characteristics of different groups[ 28 , 29 ]. In recent years, LPA has been widely applied to classify subgroups of anxiety and depression in different populations[ 30 – 32 ]. However, to the best of our knowledge, there has no study has employed LPA to investigate prenatal depression and anxiety among women with twin pregnancies in China. To address this gap, this study aims to identify the latent profiles of prenatal depression and anxiety among women pregnant with twins, and explore their influencing factors, so as to provide a basis for developing targeted interventions to improve mental health in women pregnant with twins. 2 Methods 2.1 Study design This was a cross-sectional descriptive design, which followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines (Supplementary 1). 2.2 Participants and procedures Participants were recruited from a tertiary hospital in Henan Province through a convenience sampling method from October 2024 to October 2025. Women who received routine prenatal checkups at the obstetric clinic were invited to participate in this study according to the inclusion criteria. The inclusion criteria was presented as follows: (1) age ≥ 18 years old; (2) be diagnosed with twin pregnancy by B-scan ultrasonography; (3) agreed to participant. The exclusion criteria was presented as follows: (1) women with severe medical complications; (2) women with cognitive impairment and severe mental disorders. Before the start of the survey, participants were informed the purpose of the survey and signed the informed consent. This study was conducted in accordance with the Declaration of Helsinki. A total of 340 questionnaires were initially collected, with 6 questionnaires excluded because of erroneous or logically inconsistent responses, 334 questionnaires were included in this study, the effective collection rate was 98.2%. This study was approved by the Ethics Committee of the Third Affiliated Hospital of Zhengzhou University (2024-Y106). 2.3 Measurements 2.3.1 Socio-demographic information The socio-demographic information was collected through a self-design instrument developed for this study. The socio-demographic information included demographic data (e.g., age, education level, spouse’s education level, marital status, family household income, employment status, spouse’s employment status, medical insurance payment, history of mental health) and obstetrical information (e.g., gestation age, conception, parity, relationship with spouse, whether had obstetric complications, whether had adverse obstetric history). 2.3.2 Depressive symptom The Edinburgh Postnatal Depression Scale (EPDS) is a 10-item self-report instrument designed to assess depressive symptoms among women with twin pregnancies[ 33 ]. Women were asked to answer how frequently they experienced certain feelings over the past week using a 4-point Likert scale (0–4), corresponding to the frequency categories of "never," "occasionally," "often," and "always." The total scores of EPDS ranged from 0 to 30, with higher scores indicating more severe depressive symptoms. A score of 9 or above suggests the presence of depressive mood, scores 9 ~ 12, 13 or above indicate mild depression and severe depression respectively[ 34 ]. EPDS demonstrates satisfactory sensitivity and specificity with Cronbach’s α coefficients reported 0.81 ~ 0.87, has been widely used in screening for depression among pregnant women[ 35 ]. In this study, the Cronbach’s α of EPDS was 0.821. 2.3.3. Anxiety symptom Anxiety symptoms among women with twin pregnancies was measured using the Generalized Anxiety Disorder-7 (GAD-7), a 7-item self-report scale developed by Spitzer was used to assess the frequency of generalized over the past two weeks[ 36 ]. The GAD-7 includes seven questions answered on a 4-point Likert scale from 0 (“not at all”) to 3 (“nearly every day”), yielding a total score ranging from 0 ~ 21. A total score of 5 or higher is generally considered the clinical threshold for anxiety, with scores of 5 ~ 9, 10 ~ 14, 15 or above indicating mild anxiety, moderate anxiety, and severe anxiety respectively. The GAD-7 has been widely used for anxiety screening during both pregnancy and the postpartum period due to its brevity, reliability, and validity. In this study, the Cronbach’s α of EPDS was 0.919. 2.3.4. Social support The Perceived Social Support Scale (PSSS), revised and localized by Zhang[ 37 ], was used to assess the multiple sources of social support perceived by women with twin pregnancies. The scale comprises three dimensions with a total of 12 items: family support, friend support, and other support. Responses are recorded on a 7-point Likert scale ranging from 1 ("strongly disagree") to 7 ("strongly agree"), with higher total score indicates a higher level of perceived social support. Previous studies have reported that the PSSS presents satisfactory internal consistency and test–retest reliability in prenatal women. In this study, the PSSS demonstrated good reliability with a Cronbach’s α of 0.963. 2.3.5 Coping styles The Simplified Coping Style Questionnaire (SCSQ) developed by Xie was used to measure the coping style of women with twin pregnancies[ 38 ]. SCSQ comprises two dimensions and 20 items: positive coping (12 items) and negative coping (8 items). Each item is rated from 0 ("never") to 3 ("almost always"). Total or average scores for each dimension can be calculated to reflect an individual’s typical coping styles and its frequency when facing stress. The Cronbach’s α of SCSQ was 0.905 in this study, suggesting the relatively high internal consistency. 2.4 Statistical analysis SPSS 26.0 and Mplus 8.3 were used in this study for data analysis, and the results were statistically significant difference at two-sided P < 0.05. SPSS 26.0 was used for descriptive analysis, and the data were tested for normality. Continuous variables with a normal distribution were expressed as mean ± standard deviation (M ± SD), while those with a no-normal distribution were presented as median (M) and quartile (Q). Categorical variables were described using frequencies (n) and percentages (%). In this study, Latent profile analysis (LPA) was performed using Mplus 8.3 based on the scores of depression and anxiety, so as to identify potential categories of depressive and anxiety symptoms among women with twin pregnancies. The analysis commenced with a one-class model, followed by the sequential addition of more classes to identify the most fitting model. Model fit was evaluated using criteria such as Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), and sample-size adjusted Bayesian Information Criterion (aBIC), entropy, the bootstrap likelihood ratio test (BLRT), and the Lo-Mendell-Rubin adjusted likelihood ratio test (LMRT). With lower values of AIC, BIC, and aBIC indices a better-fitting model. The entropy value ranges from 0 to 1, with higher values representing greater accuracy of classification. A statistically significant p-value ( p < 0.05) for the LMR and BLRT indicates that the k-class model fits significantly better than the (k − 1)-class model. Chi-square test, Kruskal-Wallis test, t-test, and analysis of variance (ANOVA) were conducted to compare differences in socio-demographic variables, social support, coping styles and subgroups based on the categorical results of LPA. Variables with statistical significance identified in univariate analyses were selected as independent variables, and multivariate logistic regression was performed to explore the influencing factors of distinct subgroups of anxiety and depressive symptom among women with twin pregnancies. 3 Results 3.1 Sample characteristics The participants were mostly married (97.9%), had a satisfied relationship with spouse (95.2%) and employed status of their spouses (86.8). Over two-thirds participants were below 35 years old (74.9%), had a medical insurance payment (72.8%), and conceived naturally (66.8%). More than half of participants were in the first and second trimesters of pregnancy (66.5%), reported monthly household income over 6000 yuan(62.9%), were primipara (61.1%) and employed (59.0%). Nearly half of participants had university or above degree (49.7%), while more than half of their spouses presented high school or below degree (56.3%). Only a few participants had history of adverse pregnancy (25.4%), pregnancy-related complications (16.5%), and history of mental illness (1.2%). The characteristics of women with twin pregnancies were presented in Table 1 . Table 1 Demographic information of women with twin pregnancies (n = 334) Variable N % Age <35 250 74.9 ≥ 35 84 25.1 Gestation age (week) <28 222 66.5 ≥ 28 112 33.5 Marital status Married 327 97.9 Unmarried/Divorced/Widowed 7 2.1 Ways of conception Natural conception 223 66.8 Assisted reproductive technology 111 33.2 Educational level High school or below 168 50.3 University 133 39.8 Postgraduate 33 9.9 Spouse’s education level High school or below 188 56.3 University 126 37.7 Postgraduate 20 6.0 Employment status Employed status 197 59.0 Unemployed status 137 41.0 Spouse’s employment status Employed status 290 86.8 Unemployed status 44 13.2 Monthly household income (Yuan) 4000 ~ 6000 131 39.2 6001 ~ 8000 79 23.7 >8000 124 37.1 Medical insurance payment No 91 27.2 Yes 243 72.8 Parity Primipara 204 61.1 Multiparous 130 38.9 Relationship with spouse Unsatisfied 16 4.8 Satisfied 318 95.2 Pregnancy-related complications No 279 83.5 Yes 55 16.5 History of mental illness No 330 98.8 Yes 4 1.2 History of adverse pregnancy No 249 74.6 Yes 85 25.4 3.2 Prevalence of prenatal depression and anxiety In this study, the average score of EPDS was 6.93 ± 4.21. In the sample, 33.23% women with twin pregnancies screened positive for depression, among which 26.34% women were mildly depressed, 6.89% women were moderately depressed. On the GAD-7 scale, women had an average score of 3.41 ± 3.59. The prevalence of prenatal anxiety was 34.13%, among which 33.53% women reported mild-to-moderate anxiety symptom, and 0.60% women reported severe anxiety symptom. Additionally, 24.85% women were identified as the co-morbid prenatal depressive and anxiety symptoms. (Seen in Table 2 ) Table 2 Prevalence of prenatal depression and anxiety women with twin pregnancies (n = 334) Variable Frequency Frequency Depression symptom Normal 223 66.77% Mild depression 88 26.34% Severe depression 23 6.89% Anxiety symptom Normal 220 65.87% Mild-to-moderate anxiety 112 33.53% Severe anxiety 2 0.60% 3.3 Results of latent profile analysis Fit indices for the four candidate models are presented in Table 3 , with the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), and sample-size adjusted BIC (aBIC) showing a gradual downward trend across model specifications, while entropy reached the highest value in the 4-profile model. However, both the 3- and 4-profile model were excluded from further consideration because that certain profiles within these models had disproportionately small sample proportions, and coupled with non-significant p-values (> 0.05) for the LMR test. After integrating these statistical findings with considerations of practical relevance and interpretability, the 2-profile model was ultimately selected as the optimal fitted model. (Seen in Table 3 ) Table 3 Latent profile model fitting indicators Profile AIC BIC aBIC Entropy LMR(P) BLRT(P) Probability (%) 1 11188.40 11247.98 11140.12 - - - - 2 9470.78 9668.96 9504.01 0.935 0.0025 0.0000 0.65/0.35 3 8777.54 9044.32 8822.28 0.954 0.1867 0.0000 0.55/0.40/0.05 4 8075.56 8410.940 8131.80 0.967 0.7247 0.0000 0.49/0.28/0.19/0.04 Note: AIC=Akaike information criterion; BIC=Bayesian information criterion; aBIC=sample size adjusted BIC; LMR = Lo-Mendell-Rubin likelihood ratio test; BLRT: Bootstrapped likelihood ratio test. 3.4 Naming of latent profile Based on the latent profile analysis results, the scores of the two identified profiles across the items of EPDS and GAD-7 were plotted in Fig. 1. Profile 1, accounting for 65.0% of the total sample, exhibited significantly lower scores than Profiles 2 on all items, and was labeled the “low-risk group” profile according to its score characteristics. Profile 2, which comprised 35.0% of the participants, yielded significantly higher scores than Profiles 1 across all items, and was thus designated the “high-risk group” profile. 3.5 Univariate analyses of depression and anxiety profiles Univariate analysis results revealed that the two profiles of women with twin pregnancies exhibited statistically significant differences in terms of educational level, spouse’s educational level, monthly household income (Yuan), medical insurance payment, pregnancy-related complications, history of mental illness, social support, positive coping, and negative coping. (Seen in Table 4 ) Table 4 Univariate analyses of depression and anxiety profiles (n = 334) Variable Low-risk group n(%)/M(SD)/M(Q) High-risk group n(%)/M(SD)/M(Q) χ 2 /t/Z p Age 0.002 0.963 <35 163 87 ≥ 35 55 29 Gestation age (week) 0.214 0.644 <28 143 79 ≥ 28 75 37 Marital status 0.003 0.956 Married 214 113 Unmarried/Divorced/Widowed 4 3 Ways of conception Natural conception 142 81 0.751 0.386 Assisted reproductive technology 76 35 Educational level 6.297 0.043 High school or below 99 69 University 94 39 Postgraduate 25 8 Spouse’s education level 11.178 0.004 High school or below 109 79 University 92 34 Postgraduate 17 3 Employment status 1.066 0.302 Employed status 85 52 Unemployed status 133 64 Spouse’s employment status 1.597 0.206 Employed status 25 19 Unemployed status 193 97 Monthly household income (Yuan) 7.534 0.023 4000 ~ 6000 76 55 6001 ~ 8000 50 29 >8000 92 32 Medical insurance payment 5.882 0.015 No 50 41 Yes 168 75 Parity 0.824 0.364 Primipara 137 67 Multiparous 81 49 Relationship with spouse 3.433 0.064 Unsatisfied 7 9 Satisfied 211 107 Pregnancy-related complications 7.603 0.006 No 191 88 Yes 27 28 History of mental illness 7.608 0.006 No 218 112 Yes 0 4 History of adverse pregnancy 1.397 0.237 No 167 82 Yes 51 34 Family support Friend support Other support Positive coping Negative coping 24(4) 24(5) 23(4) 27.49 ± 6.66 10.67 ± 4.59 20.5(8) 20(8) 20(7) 21.72 ± 6.75 11.53 ± 4.26 -6.470 -6.018 -5.666 7.501 -1.671 <0.001 <0.001 <0.001 <0.001 <0.001 3.6 Multivariate logistic regression of depression and anxiety profiles The result of multivariate logistic regression showed that medical insurance payment, pregnancy-related complications, family support, positive coping, and negative coping were identified as influencing factors for different profiles of prenatal depression and anxiety among women with twin pregnancies.(Seen in Table 5 ) Table 5 Multivariate logistic regression of depression and anxiety profiles (n = 334) Variables Profile 1: Low risk group VS Profile 2: High risk group B SE Wald χ 2 P OR 95%CI Medical insurance payment (Ref:no) -0.651 0.287 5.143 0.023 0.522 0.297 ~ 0.915 Pregnancy-related complications (Ref:no) 0.886 0.341 6.734 0.009 2.425 1.242 ~ 4.734 Family support -0.070 0.035 3.957 0.047 0.932 0.870 ~ 0.999 Positive coping -0.134 0.026 25.793 <0.001 0.875 0.831 ~ 0.921 Negative coping 0.153 0.035 19.280 <0.001 1.165 1.088 ~ 1.248 Note: B=Unstandardized coefficient; SE=Standard Error; Wald χ 2 = Wald chi-square test; P = P-value; OR =Odds ratio; 95%CI = 95%Confidence Interval. 4 Discussion This study employed LPA to explore the subgroups of prenatal depression and anxiety among 334 Chinese women with twin pregnancies, and identified the influencing factors of different profiles. Two profiles were rationally selected and named: low-risk group and high-risk group. The 65.0% women with twin pregnancies were sorted into low-risk group, showed low scores across all items of the EPDS and GAD-7. This indicated that this group had an overall favorable mental state, with no obvious depressive or anxiety symptoms, only had relatively higher scores on some individual items. Among the mean scores of the EPDS and GAD-7, the highest score was EPDS1(I was happy and could see the funny side of things), EPDS3(When something went wrong, I unnecessarily blamed myself) and GAD-1(Felt nervous, anxiety or urgent), GAD-3(Worrying too much about various things).The former may stem from transient feelings caused by pregnancy hormone fluctuations and physical fatigue; the latter may be due to the reasonable concerns about the specificity of twin pregnancies (e.g., worries about fetal development and delivery difficulty)[ 39 ]. Although the scores of the low-risk group remained well below the clinical symptom threshold and were not accompanied by a concurrent rise in other item scores, this group shouldn’t be ignored because these individuals may transition to high-risk level with the emergence of risks associated with twin pregnancies. As the profile with the most significant proportion, it is essential to provide continuous monitoring through routine prenatal psychological screenings, health education, and targeted interventions to prevent them transitioning to high-risk group, and such measures should focus on items with higher scores. The high-risk group, accounting for 35.0% of the total sample, exhibited significantly higher scores across all items of the EPDS and GAD-7, 24.85% of women were comorbid with both depressive and anxiety symptoms, and 7.78% of women expressed suicidal ideation, which should be of the core population in urgent need of prioritized intervention. Among the mean scores of the two scales items, the score discrepancy in GAD-7 between the low-risk group and the high-risk group was more pronounced, and the high-risk group obtained the highest scores on EPDS1(I was happy and could see the funny side of things), EPDS4(I felt anxious or worried without any reasons) and GAD-1(Felt nervous, anxiety or urgent), GAD-4(It was hard to relax). These indicated that this group not only suffered from severe emotional distress, but also the most pronounced feelings of uncontrollable anxiety and persistent worry, and anhedonia. This not only was related to the physiological and obstetric specificity of twin pregnancies but also could be explained by characteristics of high-risk group (e.g., presence of pregnancy-related complications, lack of medical insurance), which made it difficult for them to effectively alleviate the multiple pressures of pregnancy, thereby exacerbating anxiety and depressive symptoms[ 23 , 39 ]. This study underscores the critical need for early screening and intervention of suicidal ideation in high-risk group, which aligns with the guidelines and findings that recommend screening for both mental disorders and suicidal risk when pregnant women first contacted with primary care providers[ 40 – 42 ]. Moreover, health care providers should hold regular lectures for women to share the knowledge and skills to identify and manage negative emotions, and provide targeted interventions such as cognitive behavioral therapy and mindfulness-based stress to correct irrational cognitions. This study found that those women without medical insurance were more likely to be categorized into the high-risk group, which was consistent with previous research[ 43 ]. Compared with singleton pregnancies, women with twin pregnancies usually face with higher medical expenses from prenatal examinations, treatment, and neonatal care[ 44 ]. As a result, women without medical insurance maybe unable to sustain heavy self-paid medical expenses, increasing their worry and stress and subsequently leading to heavier psychological burden. Additionally, women without medical insurance have limited healthcare accessibility and continuity, which may lead to delayed or reduced necessary prenatal examinations[ 45 ]. This insufficient screening and management of complications further amplifies the uncertainty and fear regarding pregnancy outcomes. Therefore, medical insurance status should be routinely incorporated into perinatal psychological risks assessment to identify high-risk group. Moreover, this result also highlights the important supporting role of social security policies in perinatal mental health, and also suggests that it is necessary to improve the medical insurance preferential policies targeting women with twin pregnancies, so as to alleviate their economic concerns and indirectly reduce the risk of mental illnesses. In this study, we found that women with twin pregnancies who had pregnancy-related complications were more likely to be classified into the high-risk group. This finding was consistent with previous studies[ 23 ], which identified pregnancy-related complications as a core risk factor for prenatal anxiety and depression among women with twin pregnancies. The potential explanation is that as high-risk pregnancy, twin pregnancies have a significantly higher incidence of complications than singleton pregnancies[ 46 , 47 ]. The presence of complications is regarded as a stressful life event and psychological burden, because women not only would suffer from persistent concerns about maternal health and fetal development but also impose additional mental burdens due to necessary therapeutic interventions, which is favourable to trigger or exacerbate depressive or anxiety symptoms. This finding indicates that obstetric healthcare professionals should strengthen the prediction, screening, and management of pregnancy-related complications in twin pregnancies, which is a key factor in reducing the risk of prenatal depression and anxiety among women with twin pregnancies. Family support, as a core dimension of perceived social support, had been confirmed as a critical protective factor against prenatal depression and anxiety among women with twin pregnancies in other studies[ 48 , 49 ]. Previous studies have confirmed that adequate family support could provide women with emotional comport and social resources, enhance women’s psychological resilience and personal coping capacity, help them cope with stressful events more easily and more successfully adjust to motherhood, thereby reducing the risk of developing perinatal mental health problems[ 50 , 51 ]. Twin pregnancy is associated with significant physiological, economic, and caregiving burdens, family support plays a more important role in this special group. Notably, the low-risk group also exhibited relatively higher scores on specific depression and anxiety items, indicating that even women with favorable mental states, family support is also needed to maintain psychological resilience. This finding underscores the need for healthcare providers to identify women with inadequate family support as high risk of mental health problems, and conduct targeted follow-up. Moreover, family members especially spouses should be encouraged to attend prenatal health education programs to enhance the coping resources and resilience of the family system. The negative coping styles and the absence of positive coping styles significantly increased the likelihood of being classified into the high-risk group, which was consistent with previous research findings among women with singleton[ 52 , 53 ]. Coping style is defined as the totality of cognitive, emotional, and behavioral responses displayed by an individual when confronting stressful events, including positive coping and negative coping[ 54 ]. According to the stress and coping theoretical model[ 54 ], individuals were prone to experiencing negative emotions when confronted with unmanageable stressors. Twin pregnancy is widely recognized as a highly stressful event, although women adopt negative coping strategies could relive distress temporarily, it fails to mitigate the persistent stressors due to the complexity of twin pregnancies, ultimately leading to cumulative emotional exhaustion and exacerbating depressive and anxious symptoms. In contrast, women who adopt positive coping styles could enable them to assess stressors more rationally, and mobilize internal resources and external support to resolve difficulties, thereby buffering the impact of pregnancy-related stress on mental well-being[ 55 ]. Therefore, healthcare providers should encourage women with twin pregnancies to adopt positive coping strategies to cope with negative emotions, and further explore the interaction mechanisms between coping styles and other influencing factors to provide basis for developing precise interventions. 5 Strengths sand Limitations A key strength of the current study is its adoption of LPA, an individual-centered approach, to explore the subgroups of prenatal depression and anxiety among women with twin pregnancies, which overcomes the limitations of traditional variable-centered research and enhances the specificity and targeting of subsequent interventions for this high-risk obstetric population. This study also has several limitations that need to be acknowledged. Firstly, the cross-sectional design prevents the exploration of causal relationships between the identified influencing factors and the latent profiles of prenatal depression and anxiety, as well as the dynamic changes in emotional symptoms throughout the perinatal period. Future studies could adopt intensive longitudinal designs to track the trajectory of latent profiles and clarify the causal mechanisms underlying these relationships. Secondly, the participants were recruited solely from a tertiary hospital in Henan Province using a convenience sampling method, which may limit the generalizability of the findings. Future multi-center research with diverse socioeconomic backgrounds and healthcare settings would improve the external validity of the results. Finally, due to study restrictions, some influential psycho-social factors (e.g., personality traits, resilience, self-efficacy) were not included. These variables may play important roles in shaping the latent profiles of prenatal depression and anxiety, and should be taken into account in future studies. 6 Conclusion Our study classified prenatal depression and anxiety in women with twin pregnancies into two distinct subgroups (low-risk and high-risk group), and identified key factors affecting different profiles, which provides a solid empirical basis for implementing personalized mental health management strategies based on these latent profiles. More importantly, we need to pay greater attention to the mental health needs of women with twin pregnancies, and develop more comprehensive clinical guidelines and social support policies to safeguard maternal and infant health. Abbreviations EPDS: Edinburgh Postnatal Depression Scale GAD-7:Generalized Anxiety Disorder-7 LPA : Latent profile analysis PSSS: Perceived Social Support Scale SCSQ: Simplified Coping Style Questionnaire M±SD: Mean±Standard deviation Q: Quartile AIC: Akaike Information Criterion BIC: Bayesian Information Criterion aBIC: adjusted Bayesian Information Criterion BLRT: Bootstrap Likelihood Ratio Test LMRT: Lo-Mendell-Rubin adjusted likelihood ratio test ANOVA: Analysis of variance Declarations Funding This work was supported by Henan Provincial Medical Science and Technique Program of China (LHGJ20240346, LHGJ20220551). Author contributions All authors contributed to this manuscript. Sasa Huang conceived, planned, and designed the study. Hongxia Cui, Mingchen Fu, Liu Yang, Shuanghui Zhu, Hui Guo, and Min Guo collected the data. Ge Du and Peili Zhang checked the quality of the data. Sasa Huang and Dongqi Yang analyzed the data. Sasa Huang wrote the first draft manuscript. Dongsun Chen and Bing Lun revised the manuscript. All authors approved the submitted manuscript. Ethics approval and consent to participate The study has been reviewed and approved by the Ethics Committee of the Third Affiliated Hospital of Zhengzhou University (2024-Y106). Informed consent was obtained by all participants. Data availability The datasets are available from the corresponding author upon reasonable request. Declaration of Competing Interests The authors declare no competing interests. Acknowledgments The authors are grateful to all participants and nurses and obstetricians at the Third Affiliated Hospital of Zhengzhou University for their support of this investigation. Clinical trial number: not applicable References Pardo C, Watson B, Pinkhasov O, Afable A: Social determinants of perinatal mental health. Seminars in perinatology 2024, 48(6):151946. Alves SP, Costa T, Ribeiro I, Néné M, Sequeira C: Perinatal mental health counselling programme: A scoping review. Patient education and counseling 2023, 106:170-179. Bhamani SS, Arthur D, Van Parys AS, Letourneau N, Wagnild G, Premji SS, Asad N, Degomme O: Resilience and prenatal mental health in Pakistan: a qualitative inquiry. BMC pregnancy and childbirth 2022, 22(1):839. Aziz HA, Yahya HDB, Ang WW, Lau Y: Global prevalence of depression, anxiety, and stress symptoms in different trimesters of pregnancy: A meta-analysis and meta-regression. Journal of psychiatric research 2025, 181:528-546. Meng W, Shalayiding S, Wang X, Sailike B, Jiang T: Relationship between prenatal anxiety, depression, pregnancy stress and their social determinants. BMC psychology 2025, 13(1):905. Scrandis DA, Scrandis KS: Perinatal depression and anxiety. The Nurse practitioner 2024, 49(8):29-33. Morais A, Pasion R, Pinto TM, Ciuffo G, Ionio C, Costa R, Jongenelen I, Lamela D: Perinatal Anxiety and Depressive Symptoms and Maternal Parenting Behavior During the First Three Years Postpartum: A Systematic Review. Depression and anxiety 2025, 2025:1801371. Mathiasen S, Parsons CE, Fusaroli R, Paavonen EJ, Karlsson H, Karlsson L: Maternal depression and anxiety symptoms across pregnancy and the postnatal period: Modest associations between depression symptoms and infant sleep outcomes. Sleep medicine 2023, 112:291-300. Kaydırak M, Yılmaz B, Demir A, Oskay Ü: The relationships between prenatal attachment, maternal anxiety, and postpartum depression: A longitudinal study. Perspectives in psychiatric care 2022, 58(2):715-723. Bone JN, Joseph KS, Magee LA, Wang LQ, John S, Bedaiwy MA, Mayer C, Lisonkova S: Obesity, Twin Pregnancy, and the Role of Assisted Reproductive Technology. JAMA network open 2024, 7(1):e2350934. Chen S, Zhou Y, Mu Q, Wang Y: The interaction effect of pre-pregnancy body mass index and maternal age on the risk of pregnancy complications in twin pregnancies after assisted reproductive technology. The journal of maternal-fetal & neonatal medicine : the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstet 2023, 36(2):2271623. Qazi G: Obstetric and perinatal outcome of multiple pregnancy. Journal of the College of Physicians and Surgeons--Pakistan : JCPSP 2011, 21(3):142-145. Conde-Agudelo A, Belizán JM: Maternal morbidity and mortality associated with interpregnancy interval: cross sectional study. BMJ (Clinical research ed) 2000, 321(7271):1255-1259. Martin JA, Hamilton BE, Osterman MJ: Three decades of twin births in the United States, 1980-2009. NCHS data brief 2012(80):1-8. Korb D, Schmitz T, Seco A, Goffinet F, Deneux-Tharaux C: Risk factors and high-risk subgroups of severe acute maternal morbidity in twin pregnancy: A population-based study. PloS one 2020, 15(2):e0229612. Getachew T, Negash A, Debella A, Yadeta E, Lemi M, Balis B, Balcha T, Bekele H, Abdurke M, Alemu A et al : Prevalence and adverse outcomes of twin pregnancy in Eastern Africa: a systematic review and meta-analysis. BMC pregnancy and childbirth 2024, 24(1):169. Russo FM, Pozzi E, Pelizzoni F, Todyrenchuk L, Bernasconi DP, Cozzolino S, Vergani P: Stillbirths in singletons, dichorionic and monochorionic twins: a comparison of risks and causes. European journal of obstetrics, gynecology, and reproductive biology 2013, 170(1):131-136. NH C: Analysis of the Report on Medical Service and Quality Safety of Obstetrics in China. (2023 Edition) [EB/OL]. (2024-01-31). . https://wwwobqccorgcn/#/testing ? 2024. Simpson LL: Update on Management and Outcomes of Monochorionic Twin Pregnancies. Obstetrics and gynecology 2025, 145(5):486-502. Lapinsky SC, Ray JG, Brown HK, Murphy KE, Kaster TS, Vigod SN: Twin pregnancy and severe maternal mental illness: a Canadian population-based cohort study. Archives of women's mental health 2023, 26(1):57-66. Wang W, Wen L, Zhang Y, Wang L, Wang L, Chen Z, Zhang L, Zhang C, Li J, Tong C et al : Maternal prenatal stress and its effects on primary pregnancy outcomes in twin pregnancies. Journal of psychosomatic obstetrics and gynaecology 2020, 41(3):198-204. Roman A, Ramirez A, Fox NS: Prevention of preterm birth in twin pregnancies. American journal of obstetrics & gynecology MFM 2022, 4(2s):100551. Zhou Y, Huang J, Baker PN, Liao B, Yu X: The prevalence and associated factors of prenatal depression and anxiety in twin pregnancy: a cross-sectional study in Chongqing, China. BMC pregnancy and childbirth 2022, 22(1):877. Zeng S: Study on Influencing Factors of Anxiety and Depressionand Pregnancy Outcomes in Twin Pregnancies. Jianghan University; 2025. Zhou Y: The mental health of women pregnant with twins and the effect of mindfulness group therap. Chongqing Medical University; 2023. Xue S, Lu A, Chen W, Li J, Ke X, An Y: A latent profile analysis and network analysis of anxiety and depression symptoms in Chinese widowed elderly. Journal of affective disorders 2024, 366:172-180. Wang J, Chen J, Wang P, Zhang S, Li Q, Lu S, Xiao J: Identifying Internet addiction profiles among adolescents using latent profile analysis: Relations to aggression, depression, and anxiety. Journal of affective disorders 2024, 359:78-85. Lanza ST, Collins LM, Lemmon DR, Schafer JL: PROC LCA: A SAS Procedure for Latent Class Analysis. Structural Equation Modeling: A Multidisciplinary Journal 2007, 14(4):671-694. Wang Y, Kim E, Yi Z: Robustness of Latent Profile Analysis to Measurement Noninvariance Between Profiles. Educational and psychological measurement 2022, 82(1):5-28. Hou B, Zhang H: Latent profile analysis of depression among older adults living alone in China. Journal of affective disorders 2023, 325:378-385. Dai Y, Zheng Y, Hu K, Chen J, Lu S, Li Q, Xiao J: Heterogeneity in the co-occurrence of depression and anxiety among adolescents: Results of latent profile analysis. Journal of affective disorders 2024, 357:77-84. Aonso-Diego G, González-Roz A, Weidberg S, Secades-Villa R: Depression, anxiety, and stress in young adult gamers and their relationship with addictive behaviors: A latent profile analysis. Journal of affective disorders 2024, 366:254-261. Cox JL, Holden JM, Sagovsky R: Detection of postnatal depression. Development of the 10-item Edinburgh Postnatal Depression Scale. The British journal of psychiatry : the journal of mental science 1987, 150:782-786. Liu H, Huang F, Gao Y, Wang M, Lin Q, Kong Y, Zhou R, Zhang C, Chen Y: Network analysis of depression and anxiety symptoms and their associations with cognitive fusion among pregnant women. BMC psychiatry 2025, 25(1):537. Park SH, Kim JI: Predictive validity of the Edinburgh postnatal depression scale and other tools for screening depression in pregnant and postpartum women: a systematic review and meta-analysis. Archives of gynecology and obstetrics 2023, 307(5):1331-1345. Spitzer RL, Kroenke K, Williams JB, Löwe B: A brief measure for assessing generalized anxiety disorder: the GAD-7. Archives of internal medicine 2006, 166(10):1092-1097. Fan Z, Shuzhen Z, Pengji D: Evaluation of Perceived Social Support Scale used in study of social support among hospitalized patients in China. Chinese Nursing Research 2018, 32(13):2048-2052. Yaning X: A preliminary study of the reliability and validity of the Brief Coping Style Scale. Chinese Journal of Clinical Psychology 1998(02):53-54. Kertesz DP, Mor L, Dekalo A, Weiner E, Mizrachi Y, Milstein A, Barda G: Anxiety, depression and cognitive characteristics of women with twin versus singleton pregnancy. Archives of women's mental health 2025, 28(6):1563-1569. National Collaborating Centre for Mental H: National Institute for Health and Clinical Excellence: Guidance. In: Antenatal and Postnatal Mental Health: Clinical Management and Service Guidance: Updated edition. edn. Leicester (UK): British Psychological Society; 2014. ACOG Committee Opinion No. 757: Screening for Perinatal Depression. Obstetrics and gynecology 2018, 132(5):e208-e212. Xiao M, Fu B, Huang S, Hu Y, Tang G, Lei J: Trajectories of perinatal suicidal ideation from early pregnancy to six weeks postpartum and their influencing factors: A prospective longitudinal study. Psychiatry research 2023, 328:115467. Maharlouei N, Keshavarz P, Salemi N, Lankarani KB: Depression and anxiety among pregnant mothers in the initial stage of the Coronavirus Disease (COVID-19) pandemic in the southwest of Iran. Reproductive health 2021, 18(1):111. Cabrera VE, Fricke PM: Economics of Twin Pregnancies in Dairy Cattle. Animals : an open access journal from MDPI 2021, 11(2). Sia D, Tchouaket Nguemeleu E, Beogo I, Séguin C, Roch G, Cleveland J, Greenaway C: Interventions facilitating access to perinatal care for migrant women without medical insurance: A scoping review protocol. PloS one 2022, 17(3):e0265232. Narang K, Novoa VAN, Alrahmani L, Parikh P, Codsi E, Rose CH, Davies NP, Trinidad MC, Favre R, Szymanski LM et al : Management of Complicated Monochorionic Twin Gestations: An Evidence-Based Protocol. Obstetrical & gynecological survey 2021, 76(9):541-549. Evans MI, Curtis J, Evans SM, Britt DW: Fetal reduction and twins. American journal of obstetrics & gynecology MFM 2022, 4(2s):100521. Fischbein R, Meeker J, Saling JR, Chyatte M, Nicholas L: Identifying families' shared disease experiences through a qualitative analysis of online twin-to-twin transfusion syndrome stories. BMC pregnancy and childbirth 2016, 16(1):163. Benute GR, Nozzella DC, Prohaska C, Liao A, de Lucia MC, Zugaib M: Twin pregnancies: evaluation of major depression, stress, and social support. Twin research and human genetics : the official journal of the International Society for Twin Studies 2013, 16(2):629-633. Hu Y, Wang Y, Wen S, Guo X, Xu L, Chen B, Chen P, Xu X, Wang Y: Association between social and family support and antenatal depression: a hospital-based study in Chengdu, China. BMC pregnancy and childbirth 2019, 19(1):420. Huang J, Xu L, Xu Z, Luo Y, Liao B, Li Y, Shi Y: The relationship among pregnancy-related anxiety, perceived social support, family function and resilience in Chinese pregnant women: a structural equation modeling analysis. BMC women's health 2022, 22(1):546. Ren J, Jiang X, Yao J, Li X, Liu X, Pang M, Chiang CL: Depression, Social Support, and Coping Styles among Pregnant Women after the Lushan Earthquake in Ya'an, China. PloS one 2015, 10(8):e0135809. Meza-Rodríguez MDP, Farfan-Labonne B, Avila-García M, Figueroa-Damian R, Plazola-Camacho N, Pellón-Díaz G, Ríos-Flores BA, Olivas-Peña E, Leff-Gelman P, Camacho-Arroyo I: Psychological distress, anxiety, depression, stress level, and coping style in HIV-pregnant women in Mexico. BMC psychology 2023, 11(1):366. Lazarus RS, Folkman S: Stress, appraisal, and coping. Springer Publishing Company 1984. Kiyak S: The relationship of depression, anxiety, and stress with pregnancy symptoms and coping styles in pregnant women: A multi-group structural equation modeling analysis. Midwifery 2024, 136:104103. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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University","correspondingAuthor":false,"prefix":"","firstName":"Bing","middleName":"","lastName":"Lun","suffix":""},{"id":612784279,"identity":"1c0f0ae7-1f63-48d7-9d8e-fa43aa4499d6","order_by":2,"name":"Hongxia Cui","email":"","orcid":"","institution":"The Third Affiliated Hospital of Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"Hongxia","middleName":"","lastName":"Cui","suffix":""},{"id":612784281,"identity":"d3ba2ac0-6058-42a8-a980-c83fc85813be","order_by":3,"name":"Mingchen Fu","email":"","orcid":"","institution":"The Third Affiliated Hospital of Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"Mingchen","middleName":"","lastName":"Fu","suffix":""},{"id":612784282,"identity":"dd6d9272-3e32-4543-91e8-e684f9fc1e89","order_by":4,"name":"Liu Yang","email":"","orcid":"","institution":"The Third Affiliated Hospital of Zhengzhou 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16:31:02","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":88073,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e\u0026nbsp;Average scores of the two groups on depression and anxiety items.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8951651/v1/8be4dd8ba28e5e2d35947b30.png"},{"id":108083635,"identity":"3834fc18-2559-49e2-a8de-b7adafe13449","added_by":"auto","created_at":"2026-04-29 08:11:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":664714,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8951651/v1/95967b65-9225-453d-89d8-b9c2dc0137f4.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A latent profile analysis of prenatal depression and anxiety in Chinese women with twin pregnancies","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003ePregnancy represents a significant life event for women, and maternal mental health has been globally acknowledged as a critical priority in public health[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. During pregnancy, women are particularly vulnerable to suffer from mental health problems due to significant physical, emotional, and psychological changes, with a prevalence of over 10% in developed countries and over 25% in developing countries[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], among which depression and anxiety are the most common mental health issues[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. A global meta-analysis investigating the prevalence of mental health issues during pregnancy revealed that the rates of depressive and anxiety symptoms among pregnant women were 27% and 37% respectively[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. In China, a study involving 1349 pregnant women demonstrated that the proportions of those experiencing prenatal depressive symptoms reached 19.2%, with anxiety symptoms showing a slightly higher prevalence at 23.7%[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Numerous studies have confirmed that prenatal depression and anxiety have been linked to increasing risk of maternal complications and poor birth outcomes, as well as an increased risk of cognitive and behavioral development in the offspring[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Furthermore, depression and anxiety during pregnancy is also associated with an increased incidence of postpartum psychological disorders, even lead to suicidal behaviors or infanticide in severe cases[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn recent years, with the widespread application of assisted reproductive technology and the growing number of advanced maternal age pregnancies, the incidence of twin pregnancy has increased remarkably[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Evidence has shown that the incidence of twin pregnancies has increased by 50% over the last fifty years[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].Specifically, twin pregnancy occurs 1%~2.5% in some developed countries (e.g., America, Poland) [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]and 0.6%~3% in some developing countries[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] (e.g., Asia, Africa). In China, the latest national survey involving 5686 hospitals reported that twin pregnancy accounted for approximately 1.41% of all pregnancies[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. As a high-risk obstetric condition, twin pregnancy is associated with both increased risk of maternal and neonatal complications[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Additionally, compared to those with singleton pregnancies, women with twin pregnancies faced with physiological adaptations, doubled economic burdens and caregiving responsibilities, these all leading to a greater higher prevalence of prenatal depression and anxiety[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Previous studies have shown that approximately 34.8% of women with twin pregnancies suffered from prenatal depressive symptoms and 37.1% experienced anxiety symptoms, significantly higher than women with singleton pregnancies[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Therefore, prenatal anxiety and depression among women with twin pregnancies have emerged as urgent public health concerns.\u003c/p\u003e \u003cp\u003ePrevious research on prenatal depression and anxiety mainly focus on women of singleton pregnancies, women with twin pregnancies have rarely been investigated. Existing a few researches have investigated the level of prenatal depression and anxiety among women with twin pregnancies in different regions, and analyzed the relationship between prenatal depression and anxiety and other factors[\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. However, these studies defined the level of prenatal depression and anxiety of women with twin pregnancies only based on the total score of the scale or scale boundary values[\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], ignored the significant substantial variation in symptoms presentation among heterogeneous groups of individuals. Previous studies have proven that even individuals present similar levels of anxiety or depression, there still exists differences among individuals regarding to symptom patterns and outcomes[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. This variable-centered classification not only causes the results of these studies couldn\u0026rsquo;t truly reflect the symptoms of depression and anxiety among women pregnant with twins, but also makes it difficult to develop precise interventions with different risk characteristics and affects the effectiveness of interventions. As an \u0026ldquo;individual-centered\u0026rdquo; approach, latent profile analysis (LPA) is well-suited to focus on the group heterogeneity and categorize subgroups with shared characteristics according to the response patterns, and analyzed the characteristics of different groups[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. In recent years, LPA has been widely applied to classify subgroups of anxiety and depression in different populations[\u003cspan additionalcitationids=\"CR31\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. However, to the best of our knowledge, there has no study has employed LPA to investigate prenatal depression and anxiety among women with twin pregnancies in China. To address this gap, this study aims to identify the latent profiles of prenatal depression and anxiety among women pregnant with twins, and explore their influencing factors, so as to provide a basis for developing targeted interventions to improve mental health in women pregnant with twins.\u003c/p\u003e"},{"header":"2 Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study design\u003c/h2\u003e \u003cp\u003e This was a cross-sectional descriptive design, which followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines (Supplementary 1).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Participants and procedures\u003c/h2\u003e \u003cp\u003eParticipants were recruited from a tertiary hospital in Henan Province through a convenience sampling method from October 2024 to October 2025. Women who received routine prenatal checkups at the obstetric clinic were invited to participate in this study according to the inclusion criteria. The inclusion criteria was presented as follows: (1) age\u0026thinsp;\u0026ge;\u0026thinsp;18 years old; (2) be diagnosed with twin pregnancy by B-scan ultrasonography; (3) agreed to participant. The exclusion criteria was presented as follows: (1) women with severe medical complications; (2) women with cognitive impairment and severe mental disorders. Before the start of the survey, participants were informed the purpose of the survey and signed the informed consent. This study was conducted in accordance with the Declaration of Helsinki. A total of 340 questionnaires were initially collected, with 6 questionnaires excluded because of erroneous or logically inconsistent responses, 334 questionnaires were included in this study, the effective collection rate was 98.2%. This study was approved by the Ethics Committee of the Third Affiliated Hospital of Zhengzhou University (2024-Y106).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Measurements\u003c/h2\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.3.1 Socio-demographic information\u003c/h2\u003e \u003cp\u003eThe socio-demographic information was collected through a self-design instrument developed for this study. The socio-demographic information included demographic data (e.g., age, education level, spouse\u0026rsquo;s education level, marital status, family household income, employment status, spouse\u0026rsquo;s employment status, medical insurance payment, history of mental health) and obstetrical information (e.g., gestation age, conception, parity, relationship with spouse, whether had obstetric complications, whether had adverse obstetric history).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.3.2 Depressive symptom\u003c/h2\u003e \u003cp\u003eThe Edinburgh Postnatal Depression Scale (EPDS) is a 10-item self-report instrument designed to assess depressive symptoms among women with twin pregnancies[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Women were asked to answer how frequently they experienced certain feelings over the past week using a 4-point Likert scale (0\u0026ndash;4), corresponding to the frequency categories of \"never,\" \"occasionally,\" \"often,\" and \"always.\" The total scores of EPDS ranged from 0 to 30, with higher scores indicating more severe depressive symptoms. A score of 9 or above suggests the presence of depressive mood, scores 9\u0026thinsp;~\u0026thinsp;12, 13 or above indicate mild depression and severe depression respectively[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. EPDS demonstrates satisfactory sensitivity and specificity with Cronbach\u0026rsquo;s α coefficients reported 0.81\u0026thinsp;~\u0026thinsp;0.87, has been widely used in screening for depression among pregnant women[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. In this study, the Cronbach\u0026rsquo;s α of EPDS was 0.821.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.3.3. Anxiety symptom\u003c/h2\u003e \u003cp\u003eAnxiety symptoms among women with twin pregnancies was measured using the Generalized Anxiety Disorder-7 (GAD-7), a 7-item self-report scale developed by Spitzer was used to assess the frequency of generalized over the past two weeks[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. The GAD-7 includes seven questions answered on a 4-point Likert scale from 0 (\u0026ldquo;not at all\u0026rdquo;) to 3 (\u0026ldquo;nearly every day\u0026rdquo;), yielding a total score ranging from 0\u0026thinsp;~\u0026thinsp;21. A total score of 5 or higher is generally considered the clinical threshold for anxiety, with scores of 5\u0026thinsp;~\u0026thinsp;9, 10\u0026thinsp;~\u0026thinsp;14, 15 or above indicating mild anxiety, moderate anxiety, and severe anxiety respectively. The GAD-7 has been widely used for anxiety screening during both pregnancy and the postpartum period due to its brevity, reliability, and validity. In this study, the Cronbach\u0026rsquo;s α of EPDS was 0.919.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e2.3.4. Social support\u003c/h2\u003e \u003cp\u003eThe Perceived Social Support Scale (PSSS), revised and localized by Zhang[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], was used to assess the multiple sources of social support perceived by women with twin pregnancies. The scale comprises three dimensions with a total of 12 items: family support, friend support, and other support. Responses are recorded on a 7-point Likert scale ranging from 1 (\"strongly disagree\") to 7 (\"strongly agree\"), with higher total score indicates a higher level of perceived social support. Previous studies have reported that the PSSS presents satisfactory internal consistency and test\u0026ndash;retest reliability in prenatal women. In this study, the PSSS demonstrated good reliability with a Cronbach\u0026rsquo;s α of 0.963.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e2.3.5 Coping styles\u003c/h2\u003e \u003cp\u003eThe Simplified Coping Style Questionnaire (SCSQ) developed by Xie was used to measure the coping style of women with twin pregnancies[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. SCSQ comprises two dimensions and 20 items: positive coping (12 items) and negative coping (8 items). Each item is rated from 0 (\"never\") to 3 (\"almost always\"). Total or average scores for each dimension can be calculated to reflect an individual\u0026rsquo;s typical coping styles and its frequency when facing stress. The Cronbach\u0026rsquo;s α of SCSQ was 0.905 in this study, suggesting the relatively high internal consistency.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Statistical analysis\u003c/h2\u003e \u003cp\u003eSPSS 26.0 and Mplus 8.3 were used in this study for data analysis, and the results were statistically significant difference at two-sided \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003cp\u003eSPSS 26.0 was used for descriptive analysis, and the data were tested for normality. Continuous variables with a normal distribution were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (M\u0026thinsp;\u0026plusmn;\u0026thinsp;SD), while those with a no-normal distribution were presented as median (M) and quartile (Q). Categorical variables were described using frequencies (n) and percentages (%).\u003c/p\u003e \u003cp\u003eIn this study, Latent profile analysis (LPA) was performed using Mplus 8.3 based on the scores of depression and anxiety, so as to identify potential categories of depressive and anxiety symptoms among women with twin pregnancies. The analysis commenced with a one-class model, followed by the sequential addition of more classes to identify the most fitting model. Model fit was evaluated using criteria such as Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), and sample-size adjusted Bayesian Information Criterion (aBIC), entropy, the bootstrap likelihood ratio test (BLRT), and the Lo-Mendell-Rubin adjusted likelihood ratio test (LMRT). With lower values of AIC, BIC, and aBIC indices a better-fitting model. The entropy value ranges from 0 to 1, with higher values representing greater accuracy of classification. A statistically significant p-value (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) for the LMR and BLRT indicates that the k-class model fits significantly better than the (k\u0026thinsp;\u0026minus;\u0026thinsp;1)-class model.\u003c/p\u003e \u003cp\u003eChi-square test, Kruskal-Wallis test, t-test, and analysis of variance (ANOVA) were conducted to compare differences in socio-demographic variables, social support, coping styles and subgroups based on the categorical results of LPA. Variables with statistical significance identified in univariate analyses were selected as independent variables, and multivariate logistic regression was performed to explore the influencing factors of distinct subgroups of anxiety and depressive symptom among women with twin pregnancies.\u003c/p\u003e \u003c/div\u003e"},{"header":"3 Results","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Sample characteristics\u003c/h2\u003e \u003cp\u003eThe participants were mostly married (97.9%), had a satisfied relationship with spouse (95.2%) and employed status of their spouses (86.8). Over two-thirds participants were below 35 years old (74.9%), had a medical insurance payment (72.8%), and conceived naturally (66.8%). More than half of participants were in the first and second trimesters of pregnancy (66.5%), reported monthly household income over 6000 yuan(62.9%), were primipara (61.1%) and employed (59.0%). Nearly half of participants had university or above degree (49.7%), while more than half of their spouses presented high school or below degree (56.3%). Only a few participants had history of adverse pregnancy (25.4%), pregnancy-related complications (16.5%), and history of mental illness (1.2%). The characteristics of women with twin pregnancies were presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic information of women with twin pregnancies (n\u0026thinsp;=\u0026thinsp;334)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e250\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e74.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGestation age (week)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e222\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e66.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e327\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e97.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnmarried/Divorced/Widowed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWays of conception\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNatural conception\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e223\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e66.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAssisted reproductive technology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducational level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh school or below\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e168\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUniversity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e133\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePostgraduate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSpouse\u0026rsquo;s education level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh school or below\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUniversity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePostgraduate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEmployment status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmployed status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e197\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e59.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnemployed status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e137\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSpouse\u0026rsquo;s employment status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmployed status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e290\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e86.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnemployed status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMonthly household income (Yuan)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4000\u0026thinsp;~\u0026thinsp;6000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6001\u0026thinsp;~\u0026thinsp;8000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;8000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedical insurance payment\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e243\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e72.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eParity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimipara\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e204\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e61.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultiparous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRelationship with spouse\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnsatisfied\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSatisfied\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e318\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e95.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePregnancy-related complications\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e279\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e83.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHistory of mental illness\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e330\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e98.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHistory of adverse pregnancy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e249\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e74.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Prevalence of prenatal depression and anxiety\u003c/h2\u003e \u003cp\u003eIn this study, the average score of EPDS was 6.93\u0026thinsp;\u0026plusmn;\u0026thinsp;4.21. In the sample, 33.23% women with twin pregnancies screened positive for depression, among which 26.34% women were mildly depressed, 6.89% women were moderately depressed. On the GAD-7 scale, women had an average score of 3.41\u0026thinsp;\u0026plusmn;\u0026thinsp;3.59. The prevalence of prenatal anxiety was 34.13%, among which 33.53% women reported mild-to-moderate anxiety symptom, and 0.60% women reported severe anxiety symptom. Additionally, 24.85% women were identified as the co-morbid prenatal depressive and anxiety symptoms. (Seen in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrevalence of prenatal depression and anxiety women with twin pregnancies (n\u0026thinsp;=\u0026thinsp;334)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDepression symptom\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e223\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e66.77%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild depression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26.34%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere depression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.89%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnxiety symptom\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e220\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e65.87%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild-to-moderate anxiety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e33.53%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere anxiety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.60%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Results of latent profile analysis\u003c/h2\u003e \u003cp\u003eFit indices for the four candidate models are presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, with the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), and sample-size adjusted BIC (aBIC) showing a gradual downward trend across model specifications, while entropy reached the highest value in the 4-profile model. However, both the 3- and 4-profile model were excluded from further consideration because that certain profiles within these models had disproportionately small sample proportions, and coupled with non-significant p-values (\u0026gt;\u0026thinsp;0.05) for the LMR test. After integrating these statistical findings with considerations of practical relevance and interpretability, the 2-profile model was ultimately selected as the optimal fitted model. (Seen in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLatent profile model fitting indicators\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProfile\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAIC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBIC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eaBIC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEntropy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLMR(P)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eBLRT(P)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eProbability (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11188.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11247.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11140.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9470.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9668.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9504.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.935\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.65/0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8777.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9044.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8822.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.954\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.1867\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.55/0.40/0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8075.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8410.940\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8131.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.967\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.7247\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.49/0.28/0.19/0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eNote: AIC=Akaike information criterion; BIC=Bayesian information criterion; aBIC=sample size adjusted BIC; LMR\u0026thinsp;=\u0026thinsp;Lo-Mendell-Rubin likelihood ratio test; BLRT: Bootstrapped likelihood ratio test.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\u003cp\u003e\u003cstrong\u003e3.4 Naming of latent profile\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eBased on the latent profile analysis results, the scores of the two identified profiles across the items of EPDS and GAD-7 were plotted in Fig.\u0026nbsp;1. Profile 1, accounting for 65.0% of the total sample, exhibited significantly lower scores than Profiles 2 on all items, and was labeled the \u0026ldquo;low-risk group\u0026rdquo; profile according to its score characteristics. Profile 2, which comprised 35.0% of the participants, yielded significantly higher scores than Profiles 1 across all items, and was thus designated the \u0026ldquo;high-risk group\u0026rdquo; profile.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Univariate analyses of depression and anxiety profiles\u003c/h2\u003e \u003cp\u003eUnivariate analysis results revealed that the two profiles of women with twin pregnancies exhibited statistically significant differences in terms of educational level, spouse\u0026rsquo;s educational level, monthly household income (Yuan), medical insurance payment, pregnancy-related complications, history of mental illness, social support, positive coping, and negative coping. (Seen in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariate analyses of depression and anxiety profiles (n\u0026thinsp;=\u0026thinsp;334)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow-risk group\u003c/p\u003e \u003cp\u003en(%)/M(SD)/M(Q)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHigh-risk group\u003c/p\u003e \u003cp\u003en(%)/M(SD)/M(Q)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eχ\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e/t/Z\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.963\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e163\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGestation age (week)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.644\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.956\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnmarried/Divorced/Widowed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWays of conception\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNatural conception\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.751\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.386\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAssisted reproductive technology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducational level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.297\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.043\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh school or below\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUniversity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePostgraduate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSpouse\u0026rsquo;s education level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.178\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh school or below\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUniversity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePostgraduate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEmployment status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.066\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.302\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmployed status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnemployed status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e133\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSpouse\u0026rsquo;s employment status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.597\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.206\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmployed status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnemployed status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e193\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMonthly household income (Yuan)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.534\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4000\u0026thinsp;~\u0026thinsp;6000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6001\u0026thinsp;~\u0026thinsp;8000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;8000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedical insurance payment\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.882\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e168\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eParity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.824\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.364\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimipara\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e137\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultiparous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRelationship with spouse\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.433\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.064\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnsatisfied\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSatisfied\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e211\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e107\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePregnancy-related complications\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.603\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e191\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHistory of mental illness\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.608\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e218\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHistory of adverse pregnancy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.397\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.237\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFamily support\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eFriend support\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eOther support\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003ePositive coping\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eNegative coping\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24(4)\u003c/p\u003e \u003cp\u003e24(5)\u003c/p\u003e \u003cp\u003e23(4)\u003c/p\u003e \u003cp\u003e27.49\u0026thinsp;\u0026plusmn;\u0026thinsp;6.66\u003c/p\u003e \u003cp\u003e10.67\u0026thinsp;\u0026plusmn;\u0026thinsp;4.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.5(8)\u003c/p\u003e \u003cp\u003e20(8)\u003c/p\u003e \u003cp\u003e20(7)\u003c/p\u003e \u003cp\u003e21.72\u0026thinsp;\u0026plusmn;\u0026thinsp;6.75\u003c/p\u003e \u003cp\u003e11.53\u0026thinsp;\u0026plusmn;\u0026thinsp;4.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-6.470\u003c/p\u003e \u003cp\u003e-6.018\u003c/p\u003e \u003cp\u003e-5.666\u003c/p\u003e \u003cp\u003e7.501\u003c/p\u003e \u003cp\u003e-1.671\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.6 Multivariate logistic regression of depression and anxiety profiles\u003c/h2\u003e \u003cp\u003eThe result of multivariate logistic regression showed that medical insurance payment, pregnancy-related complications, family support, positive coping, and negative coping were identified as influencing factors for different profiles of prenatal depression and anxiety among women with twin pregnancies.(Seen in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultivariate logistic regression of depression and anxiety profiles (n\u0026thinsp;=\u0026thinsp;334)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eProfile 1: Low risk group VS Profile 2: High risk group\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eB\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eSE\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWald\u003cem\u003eχ\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eOR\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003e95%CI\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedical insurance payment (Ref:no)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.651\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.287\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.522\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.297\u0026thinsp;~\u0026thinsp;0.915\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePregnancy-related complications (Ref:no)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.886\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.341\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.734\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.425\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.242\u0026thinsp;~\u0026thinsp;4.734\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily support\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.070\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.957\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.932\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.870\u0026thinsp;~\u0026thinsp;0.999\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive coping\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.793\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.875\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.831\u0026thinsp;~\u0026thinsp;0.921\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative coping\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.153\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19.280\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.165\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.088\u0026thinsp;~\u0026thinsp;1.248\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eNote: B=Unstandardized coefficient; SE=Standard Error; Wald\u003cem\u003eχ\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;Wald chi-square test; P\u0026thinsp;=\u0026thinsp;P-value; OR =Odds ratio; 95%CI\u0026thinsp;=\u0026thinsp;95%Confidence Interval.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4 Discussion","content":"\u003cp\u003eThis study employed LPA to explore the subgroups of prenatal depression and anxiety among 334 Chinese women with twin pregnancies, and identified the influencing factors of different profiles. Two profiles were rationally selected and named: low-risk group and high-risk group.\u003c/p\u003e \u003cp\u003eThe 65.0% women with twin pregnancies were sorted into low-risk group, showed low scores across all items of the EPDS and GAD-7. This indicated that this group had an overall favorable mental state, with no obvious depressive or anxiety symptoms, only had relatively higher scores on some individual items. Among the mean scores of the EPDS and GAD-7, the highest score was EPDS1(I was happy and could see the funny side of things), EPDS3(When something went wrong, I unnecessarily blamed myself) and GAD-1(Felt nervous, anxiety or urgent), GAD-3(Worrying too much about various things).The former may stem from transient feelings caused by pregnancy hormone fluctuations and physical fatigue; the latter may be due to the reasonable concerns about the specificity of twin pregnancies (e.g., worries about fetal development and delivery difficulty)[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Although the scores of the low-risk group remained well below the clinical symptom threshold and were not accompanied by a concurrent rise in other item scores, this group shouldn\u0026rsquo;t be ignored because these individuals may transition to high-risk level with the emergence of risks associated with twin pregnancies. As the profile with the most significant proportion, it is essential to provide continuous monitoring through routine prenatal psychological screenings, health education, and targeted interventions to prevent them transitioning to high-risk group, and such measures should focus on items with higher scores.\u003c/p\u003e \u003cp\u003eThe high-risk group, accounting for 35.0% of the total sample, exhibited significantly higher scores across all items of the EPDS and GAD-7, 24.85% of women were comorbid with both depressive and anxiety symptoms, and 7.78% of women expressed suicidal ideation, which should be of the core population in urgent need of prioritized intervention. Among the mean scores of the two scales items, the score discrepancy in GAD-7 between the low-risk group and the high-risk group was more pronounced, and the high-risk group obtained the highest scores on EPDS1(I was happy and could see the funny side of things), EPDS4(I felt anxious or worried without any reasons) and GAD-1(Felt nervous, anxiety or urgent), GAD-4(It was hard to relax). These indicated that this group not only suffered from severe emotional distress, but also the most pronounced feelings of uncontrollable anxiety and persistent worry, and anhedonia. This not only was related to the physiological and obstetric specificity of twin pregnancies but also could be explained by characteristics of high-risk group (e.g., presence of pregnancy-related complications, lack of medical insurance), which made it difficult for them to effectively alleviate the multiple pressures of pregnancy, thereby exacerbating anxiety and depressive symptoms[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. This study underscores the critical need for early screening and intervention of suicidal ideation in high-risk group, which aligns with the guidelines and findings that recommend screening for both mental disorders and suicidal risk when pregnant women first contacted with primary care providers[\u003cspan additionalcitationids=\"CR41\" citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Moreover, health care providers should hold regular lectures for women to share the knowledge and skills to identify and manage negative emotions, and provide targeted interventions such as cognitive behavioral therapy and mindfulness-based stress to correct irrational cognitions.\u003c/p\u003e \u003cp\u003eThis study found that those women without medical insurance were more likely to be categorized into the high-risk group, which was consistent with previous research[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Compared with singleton pregnancies, women with twin pregnancies usually face with higher medical expenses from prenatal examinations, treatment, and neonatal care[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. As a result, women without medical insurance maybe unable to sustain heavy self-paid medical expenses, increasing their worry and stress and subsequently leading to heavier psychological burden. Additionally, women without medical insurance have limited healthcare accessibility and continuity, which may lead to delayed or reduced necessary prenatal examinations[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. This insufficient screening and management of complications further amplifies the uncertainty and fear regarding pregnancy outcomes. Therefore, medical insurance status should be routinely incorporated into perinatal psychological risks assessment to identify high-risk group. Moreover, this result also highlights the important supporting role of social security policies in perinatal mental health, and also suggests that it is necessary to improve the medical insurance preferential policies targeting women with twin pregnancies, so as to alleviate their economic concerns and indirectly reduce the risk of mental illnesses.\u003c/p\u003e \u003cp\u003eIn this study, we found that women with twin pregnancies who had pregnancy-related complications were more likely to be classified into the high-risk group. This finding was consistent with previous studies[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], which identified pregnancy-related complications as a core risk factor for prenatal anxiety and depression among women with twin pregnancies. The potential explanation is that as high-risk pregnancy, twin pregnancies have a significantly higher incidence of complications than singleton pregnancies[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. The presence of complications is regarded as a stressful life event and psychological burden, because women not only would suffer from persistent concerns about maternal health and fetal development but also impose additional mental burdens due to necessary therapeutic interventions, which is favourable to trigger or exacerbate depressive or anxiety symptoms. This finding indicates that obstetric healthcare professionals should strengthen the prediction, screening, and management of pregnancy-related complications in twin pregnancies, which is a key factor in reducing the risk of prenatal depression and anxiety among women with twin pregnancies.\u003c/p\u003e \u003cp\u003eFamily support, as a core dimension of perceived social support, had been confirmed as a critical protective factor against prenatal depression and anxiety among women with twin pregnancies in other studies[\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Previous studies have confirmed that adequate family support could provide women with emotional comport and social resources, enhance women\u0026rsquo;s psychological resilience and personal coping capacity, help them cope with stressful events more easily and more successfully adjust to motherhood, thereby reducing the risk of developing perinatal mental health problems[\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Twin pregnancy is associated with significant physiological, economic, and caregiving burdens, family support plays a more important role in this special group. Notably, the low-risk group also exhibited relatively higher scores on specific depression and anxiety items, indicating that even women with favorable mental states, family support is also needed to maintain psychological resilience. This finding underscores the need for healthcare providers to identify women with inadequate family support as high risk of mental health problems, and conduct targeted follow-up. Moreover, family members especially spouses should be encouraged to attend prenatal health education programs to enhance the coping resources and resilience of the family system.\u003c/p\u003e \u003cp\u003eThe negative coping styles and the absence of positive coping styles significantly increased the likelihood of being classified into the high-risk group, which was consistent with previous research findings among women with singleton[\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. Coping style is defined as the totality of cognitive, emotional, and behavioral responses displayed by an individual when confronting stressful events, including positive coping and negative coping[\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. According to the stress and coping theoretical model[\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e], individuals were prone to experiencing negative emotions when confronted with unmanageable stressors. Twin pregnancy is widely recognized as a highly stressful event, although women adopt negative coping strategies could relive distress temporarily, it fails to mitigate the persistent stressors due to the complexity of twin pregnancies, ultimately leading to cumulative emotional exhaustion and exacerbating depressive and anxious symptoms. In contrast, women who adopt positive coping styles could enable them to assess stressors more rationally, and mobilize internal resources and external support to resolve difficulties, thereby buffering the impact of pregnancy-related stress on mental well-being[\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. Therefore, healthcare providers should encourage women with twin pregnancies to adopt positive coping strategies to cope with negative emotions, and further explore the interaction mechanisms between coping styles and other influencing factors to provide basis for developing precise interventions.\u003c/p\u003e"},{"header":"5 Strengths sand Limitations","content":"\u003cp\u003eA key strength of the current study is its adoption of LPA, an individual-centered approach, to explore the subgroups of prenatal depression and anxiety among women with twin pregnancies, which overcomes the limitations of traditional variable-centered research and enhances the specificity and targeting of subsequent interventions for this high-risk obstetric population.\u003c/p\u003e \u003cp\u003eThis study also has several limitations that need to be acknowledged. Firstly, the cross-sectional design prevents the exploration of causal relationships between the identified influencing factors and the latent profiles of prenatal depression and anxiety, as well as the dynamic changes in emotional symptoms throughout the perinatal period. Future studies could adopt intensive longitudinal designs to track the trajectory of latent profiles and clarify the causal mechanisms underlying these relationships. Secondly, the participants were recruited solely from a tertiary hospital in Henan Province using a convenience sampling method, which may limit the generalizability of the findings. Future multi-center research with diverse socioeconomic backgrounds and healthcare settings would improve the external validity of the results. Finally, due to study restrictions, some influential psycho-social factors (e.g., personality traits, resilience, self-efficacy) were not included. These variables may play important roles in shaping the latent profiles of prenatal depression and anxiety, and should be taken into account in future studies.\u003c/p\u003e"},{"header":"6 Conclusion","content":"\u003cp\u003eOur study classified prenatal depression and anxiety in women with twin pregnancies into two distinct subgroups (low-risk and high-risk group), and identified key factors affecting different profiles, which provides a solid empirical basis for implementing personalized mental health management strategies based on these latent profiles. More importantly, we need to pay greater attention to the mental health needs of women with twin pregnancies, and develop more comprehensive clinical guidelines and social support policies to safeguard maternal and infant health.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eEPDS: Edinburgh Postnatal Depression Scale\u003cbr\u003e\u0026nbsp;GAD-7:Generalized Anxiety Disorder-7\u003c/p\u003e\n\u003cp\u003eLPA : Latent profile analysis\u003c/p\u003e\n\u003cp\u003ePSSS: Perceived Social Support Scale\u003c/p\u003e\n\u003cp\u003eSCSQ: Simplified Coping Style Questionnaire\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eM\u0026plusmn;SD: Mean\u0026plusmn;Standard deviation\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eQ: Quartile\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAIC: Akaike Information Criterion\u003c/p\u003e\n\u003cp\u003eBIC: Bayesian Information Criterion\u003c/p\u003e\n\u003cp\u003eaBIC: adjusted Bayesian Information Criterion\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBLRT: Bootstrap Likelihood Ratio Test\u003c/p\u003e\n\u003cp\u003eLMRT: Lo-Mendell-Rubin adjusted likelihood ratio test\u003c/p\u003e\n\u003cp\u003eANOVA: Analysis of variance\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by Henan Provincial Medical Science and Technique Program of China (LHGJ20240346, LHGJ20220551).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed to this manuscript. Sasa Huang conceived, planned, and designed the study. Hongxia Cui, Mingchen Fu, Liu Yang, Shuanghui Zhu, Hui Guo, and Min Guo collected the data. Ge Du and Peili Zhang checked the quality of the data. Sasa Huang and Dongqi Yang analyzed the data. Sasa Huang wrote the first draft manuscript. Dongsun Chen and Bing Lun revised the manuscript. All authors approved the submitted manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study has been reviewed and approved by the Ethics Committee of the Third Affiliated Hospital of Zhengzhou University (2024-Y106). Informed consent was obtained by all participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of Competing Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors are grateful to all participants and nurses and obstetricians at the Third Affiliated Hospital of Zhengzhou University for their support of this investigation.\u003c/p\u003e\n\u003cp\u003eClinical trial number: not applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003ePardo C, Watson B, Pinkhasov O, Afable A: Social determinants of perinatal mental health. \u003cem\u003eSeminars in perinatology \u003c/em\u003e2024, 48(6):151946.\u003c/li\u003e\n\u003cli\u003eAlves SP, Costa T, Ribeiro I, N\u0026eacute;n\u0026eacute; M, Sequeira C: Perinatal mental health counselling programme: A scoping review. \u003cem\u003ePatient education and counseling \u003c/em\u003e2023, 106:170-179.\u003c/li\u003e\n\u003cli\u003eBhamani SS, Arthur D, Van Parys AS, Letourneau N, Wagnild G, Premji SS, Asad N, Degomme O: Resilience and prenatal mental health in Pakistan: a qualitative inquiry. \u003cem\u003eBMC pregnancy and childbirth \u003c/em\u003e2022, 22(1):839.\u003c/li\u003e\n\u003cli\u003eAziz HA, Yahya HDB, Ang WW, Lau Y: Global prevalence of depression, anxiety, and stress symptoms in different trimesters of pregnancy: A meta-analysis and meta-regression. \u003cem\u003eJournal of psychiatric research \u003c/em\u003e2025, 181:528-546.\u003c/li\u003e\n\u003cli\u003eMeng W, Shalayiding S, Wang X, Sailike B, Jiang T: Relationship between prenatal anxiety, depression, pregnancy stress and their social determinants. \u003cem\u003eBMC psychology \u003c/em\u003e2025, 13(1):905.\u003c/li\u003e\n\u003cli\u003eScrandis DA, Scrandis KS: Perinatal depression and anxiety. \u003cem\u003eThe Nurse practitioner \u003c/em\u003e2024, 49(8):29-33.\u003c/li\u003e\n\u003cli\u003eMorais A, Pasion R, Pinto TM, Ciuffo G, Ionio C, Costa R, Jongenelen I, Lamela D: Perinatal Anxiety and Depressive Symptoms and Maternal Parenting Behavior During the First Three Years Postpartum: A Systematic Review. \u003cem\u003eDepression and anxiety \u003c/em\u003e2025, 2025:1801371.\u003c/li\u003e\n\u003cli\u003eMathiasen S, Parsons CE, Fusaroli R, Paavonen EJ, Karlsson H, Karlsson L: Maternal depression and anxiety symptoms across pregnancy and the postnatal period: Modest associations between depression symptoms and infant sleep outcomes. \u003cem\u003eSleep medicine \u003c/em\u003e2023, 112:291-300.\u003c/li\u003e\n\u003cli\u003eKaydırak M, Yılmaz B, Demir A, Oskay \u0026Uuml;: The relationships between prenatal attachment, maternal anxiety, and postpartum depression: A longitudinal study. \u003cem\u003ePerspectives in psychiatric care \u003c/em\u003e2022, 58(2):715-723.\u003c/li\u003e\n\u003cli\u003eBone JN, Joseph KS, Magee LA, Wang LQ, John S, Bedaiwy MA, Mayer C, Lisonkova S: Obesity, Twin Pregnancy, and the Role of Assisted Reproductive Technology. \u003cem\u003eJAMA network open \u003c/em\u003e2024, 7(1):e2350934.\u003c/li\u003e\n\u003cli\u003eChen S, Zhou Y, Mu Q, Wang Y: The interaction effect of pre-pregnancy body mass index and maternal age on the risk of pregnancy complications in twin pregnancies after assisted reproductive technology. \u003cem\u003eThe journal of maternal-fetal \u0026amp; neonatal medicine : the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstet \u003c/em\u003e2023, 36(2):2271623.\u003c/li\u003e\n\u003cli\u003eQazi G: Obstetric and perinatal outcome of multiple pregnancy. \u003cem\u003eJournal of the College of Physicians and Surgeons--Pakistan : JCPSP \u003c/em\u003e2011, 21(3):142-145.\u003c/li\u003e\n\u003cli\u003eConde-Agudelo A, Beliz\u0026aacute;n JM: Maternal morbidity and mortality associated with interpregnancy interval: cross sectional study. \u003cem\u003eBMJ (Clinical research ed) \u003c/em\u003e2000, 321(7271):1255-1259.\u003c/li\u003e\n\u003cli\u003eMartin JA, Hamilton BE, Osterman MJ: Three decades of twin births in the United States, 1980-2009. \u003cem\u003eNCHS data brief \u003c/em\u003e2012(80):1-8.\u003c/li\u003e\n\u003cli\u003eKorb D, Schmitz T, Seco A, Goffinet F, Deneux-Tharaux C: Risk factors and high-risk subgroups of severe acute maternal morbidity in twin pregnancy: A population-based study. \u003cem\u003ePloS one \u003c/em\u003e2020, 15(2):e0229612.\u003c/li\u003e\n\u003cli\u003eGetachew T, Negash A, Debella A, Yadeta E, Lemi M, Balis B, Balcha T, Bekele H, Abdurke M, Alemu A\u003cem\u003e et al\u003c/em\u003e: Prevalence and adverse outcomes of twin pregnancy in Eastern Africa: a systematic review and meta-analysis. \u003cem\u003eBMC pregnancy and childbirth \u003c/em\u003e2024, 24(1):169.\u003c/li\u003e\n\u003cli\u003eRusso FM, Pozzi E, Pelizzoni F, Todyrenchuk L, Bernasconi DP, Cozzolino S, Vergani P: Stillbirths in singletons, dichorionic and monochorionic twins: a comparison of risks and causes. \u003cem\u003eEuropean journal of obstetrics, gynecology, and reproductive biology \u003c/em\u003e2013, 170(1):131-136.\u003c/li\u003e\n\u003cli\u003eNH C: Analysis of the Report on Medical Service and Quality Safety of Obstetrics in China. (2023 Edition) [EB/OL]. (2024-01-31). .\u003cem\u003ehttps://wwwobqccorgcn/#/testing\u003c/em\u003e\u003cem\u003e? \u003c/em\u003e2024.\u003c/li\u003e\n\u003cli\u003eSimpson LL: Update on Management and Outcomes of Monochorionic Twin Pregnancies. \u003cem\u003eObstetrics and gynecology \u003c/em\u003e2025, 145(5):486-502.\u003c/li\u003e\n\u003cli\u003eLapinsky SC, Ray JG, Brown HK, Murphy KE, Kaster TS, Vigod SN: Twin pregnancy and severe maternal mental illness: a Canadian population-based cohort study. \u003cem\u003eArchives of women\u0026apos;s mental health \u003c/em\u003e2023, 26(1):57-66.\u003c/li\u003e\n\u003cli\u003eWang W, Wen L, Zhang Y, Wang L, Wang L, Chen Z, Zhang L, Zhang C, Li J, Tong C\u003cem\u003e et al\u003c/em\u003e: Maternal prenatal stress and its effects on primary pregnancy outcomes in twin pregnancies. \u003cem\u003eJournal of psychosomatic obstetrics and gynaecology \u003c/em\u003e2020, 41(3):198-204.\u003c/li\u003e\n\u003cli\u003eRoman A, Ramirez A, Fox NS: Prevention of preterm birth in twin pregnancies. \u003cem\u003eAmerican journal of obstetrics \u0026amp; gynecology MFM \u003c/em\u003e2022, 4(2s):100551.\u003c/li\u003e\n\u003cli\u003eZhou Y, Huang J, Baker PN, Liao B, Yu X: The prevalence and associated factors of prenatal depression and anxiety in twin pregnancy: a cross-sectional study in Chongqing, China. \u003cem\u003eBMC pregnancy and childbirth \u003c/em\u003e2022, 22(1):877.\u003c/li\u003e\n\u003cli\u003eZeng S: Study on Influencing Factors of Anxiety and Depressionand Pregnancy Outcomes in Twin Pregnancies. Jianghan University; 2025.\u003c/li\u003e\n\u003cli\u003eZhou Y: The mental health of women pregnant with twins and the effect of mindfulness group therap. Chongqing Medical University; 2023.\u003c/li\u003e\n\u003cli\u003eXue S, Lu A, Chen W, Li J, Ke X, An Y: A latent profile analysis and network analysis of anxiety and depression symptoms in Chinese widowed elderly. \u003cem\u003eJournal of affective disorders \u003c/em\u003e2024, 366:172-180.\u003c/li\u003e\n\u003cli\u003eWang J, Chen J, Wang P, Zhang S, Li Q, Lu S, Xiao J: Identifying Internet addiction profiles among adolescents using latent profile analysis: Relations to aggression, depression, and anxiety. \u003cem\u003eJournal of affective disorders \u003c/em\u003e2024, 359:78-85.\u003c/li\u003e\n\u003cli\u003eLanza ST, Collins LM, Lemmon DR, Schafer JL: PROC LCA: A SAS Procedure for Latent Class Analysis. \u003cem\u003eStructural Equation Modeling: A Multidisciplinary Journal \u003c/em\u003e2007, 14(4):671-694.\u003c/li\u003e\n\u003cli\u003eWang Y, Kim E, Yi Z: Robustness of Latent Profile Analysis to Measurement Noninvariance Between Profiles. \u003cem\u003eEducational and psychological measurement \u003c/em\u003e2022, 82(1):5-28.\u003c/li\u003e\n\u003cli\u003eHou B, Zhang H: Latent profile analysis of depression among older adults living alone in China. \u003cem\u003eJournal of affective disorders \u003c/em\u003e2023, 325:378-385.\u003c/li\u003e\n\u003cli\u003eDai Y, Zheng Y, Hu K, Chen J, Lu S, Li Q, Xiao J: Heterogeneity in the co-occurrence of depression and anxiety among adolescents: Results of latent profile analysis. \u003cem\u003eJournal of affective disorders \u003c/em\u003e2024, 357:77-84.\u003c/li\u003e\n\u003cli\u003eAonso-Diego G, Gonz\u0026aacute;lez-Roz A, Weidberg S, Secades-Villa R: Depression, anxiety, and stress in young adult gamers and their relationship with addictive behaviors: A latent profile analysis. \u003cem\u003eJournal of affective disorders \u003c/em\u003e2024, 366:254-261.\u003c/li\u003e\n\u003cli\u003eCox JL, Holden JM, Sagovsky R: Detection of postnatal depression. Development of the 10-item Edinburgh Postnatal Depression Scale. \u003cem\u003eThe British journal of psychiatry : the journal of mental science \u003c/em\u003e1987, 150:782-786.\u003c/li\u003e\n\u003cli\u003eLiu H, Huang F, Gao Y, Wang M, Lin Q, Kong Y, Zhou R, Zhang C, Chen Y: Network analysis of depression and anxiety symptoms and their associations with cognitive fusion among pregnant women. \u003cem\u003eBMC psychiatry \u003c/em\u003e2025, 25(1):537.\u003c/li\u003e\n\u003cli\u003ePark SH, Kim JI: Predictive validity of the Edinburgh postnatal depression scale and other tools for screening depression in pregnant and postpartum women: a systematic review and meta-analysis. \u003cem\u003eArchives of gynecology and obstetrics \u003c/em\u003e2023, 307(5):1331-1345.\u003c/li\u003e\n\u003cli\u003eSpitzer RL, Kroenke K, Williams JB, L\u0026ouml;we B: A brief measure for assessing generalized anxiety disorder: the GAD-7. \u003cem\u003eArchives of internal medicine \u003c/em\u003e2006, 166(10):1092-1097.\u003c/li\u003e\n\u003cli\u003eFan Z, Shuzhen Z, Pengji D: Evaluation of Perceived Social Support Scale used in study of social support among hospitalized patients in China. \u003cem\u003eChinese Nursing Research \u003c/em\u003e2018, 32(13):2048-2052.\u003c/li\u003e\n\u003cli\u003eYaning X: A preliminary study of the reliability and validity of the Brief Coping Style Scale. \u003cem\u003eChinese Journal of Clinical Psychology \u003c/em\u003e1998(02):53-54.\u003c/li\u003e\n\u003cli\u003eKertesz DP, Mor L, Dekalo A, Weiner E, Mizrachi Y, Milstein A, Barda G: Anxiety, depression and cognitive characteristics of women with twin versus singleton pregnancy. \u003cem\u003eArchives of women\u0026apos;s mental health \u003c/em\u003e2025, 28(6):1563-1569.\u003c/li\u003e\n\u003cli\u003eNational Collaborating Centre for Mental H: National Institute for Health and Clinical Excellence: Guidance. In: \u003cem\u003eAntenatal and Postnatal Mental Health: Clinical Management and Service Guidance: Updated edition.\u003c/em\u003e edn. Leicester (UK): British Psychological Society; 2014.\u003c/li\u003e\n\u003cli\u003eACOG Committee Opinion No. 757: Screening for Perinatal Depression. \u003cem\u003eObstetrics and gynecology \u003c/em\u003e2018, 132(5):e208-e212.\u003c/li\u003e\n\u003cli\u003eXiao M, Fu B, Huang S, Hu Y, Tang G, Lei J: Trajectories of perinatal suicidal ideation from early pregnancy to six weeks postpartum and their influencing factors: A prospective longitudinal study. \u003cem\u003ePsychiatry research \u003c/em\u003e2023, 328:115467.\u003c/li\u003e\n\u003cli\u003eMaharlouei N, Keshavarz P, Salemi N, Lankarani KB: Depression and anxiety among pregnant mothers in the initial stage of the Coronavirus Disease (COVID-19) pandemic in the southwest of Iran. \u003cem\u003eReproductive health \u003c/em\u003e2021, 18(1):111.\u003c/li\u003e\n\u003cli\u003eCabrera VE, Fricke PM: Economics of Twin Pregnancies in Dairy Cattle. \u003cem\u003eAnimals : an open access journal from MDPI \u003c/em\u003e2021, 11(2).\u003c/li\u003e\n\u003cli\u003eSia D, Tchouaket Nguemeleu E, Beogo I, S\u0026eacute;guin C, Roch G, Cleveland J, Greenaway C: Interventions facilitating access to perinatal care for migrant women without medical insurance: A scoping review protocol. \u003cem\u003ePloS one \u003c/em\u003e2022, 17(3):e0265232.\u003c/li\u003e\n\u003cli\u003eNarang K, Novoa VAN, Alrahmani L, Parikh P, Codsi E, Rose CH, Davies NP, Trinidad MC, Favre R, Szymanski LM\u003cem\u003e et al\u003c/em\u003e: Management of Complicated Monochorionic Twin Gestations: An Evidence-Based Protocol. \u003cem\u003eObstetrical \u0026amp; gynecological survey \u003c/em\u003e2021, 76(9):541-549.\u003c/li\u003e\n\u003cli\u003eEvans MI, Curtis J, Evans SM, Britt DW: Fetal reduction and twins. \u003cem\u003eAmerican journal of obstetrics \u0026amp; gynecology MFM \u003c/em\u003e2022, 4(2s):100521.\u003c/li\u003e\n\u003cli\u003eFischbein R, Meeker J, Saling JR, Chyatte M, Nicholas L: Identifying families\u0026apos; shared disease experiences through a qualitative analysis of online twin-to-twin transfusion syndrome stories. \u003cem\u003eBMC pregnancy and childbirth \u003c/em\u003e2016, 16(1):163.\u003c/li\u003e\n\u003cli\u003eBenute GR, Nozzella DC, Prohaska C, Liao A, de Lucia MC, Zugaib M: Twin pregnancies: evaluation of major depression, stress, and social support. \u003cem\u003eTwin research and human genetics : the official journal of the International Society for Twin Studies \u003c/em\u003e2013, 16(2):629-633.\u003c/li\u003e\n\u003cli\u003eHu Y, Wang Y, Wen S, Guo X, Xu L, Chen B, Chen P, Xu X, Wang Y: Association between social and family support and antenatal depression: a hospital-based study in Chengdu, China. \u003cem\u003eBMC pregnancy and childbirth \u003c/em\u003e2019, 19(1):420.\u003c/li\u003e\n\u003cli\u003eHuang J, Xu L, Xu Z, Luo Y, Liao B, Li Y, Shi Y: The relationship among pregnancy-related anxiety, perceived social support, family function and resilience in Chinese pregnant women: a structural equation modeling analysis. \u003cem\u003eBMC women\u0026apos;s health \u003c/em\u003e2022, 22(1):546.\u003c/li\u003e\n\u003cli\u003eRen J, Jiang X, Yao J, Li X, Liu X, Pang M, Chiang CL: Depression, Social Support, and Coping Styles among Pregnant Women after the Lushan Earthquake in Ya\u0026apos;an, China. \u003cem\u003ePloS one \u003c/em\u003e2015, 10(8):e0135809.\u003c/li\u003e\n\u003cli\u003eMeza-Rodr\u0026iacute;guez MDP, Farfan-Labonne B, Avila-Garc\u0026iacute;a M, Figueroa-Damian R, Plazola-Camacho N, Pell\u0026oacute;n-D\u0026iacute;az G, R\u0026iacute;os-Flores BA, Olivas-Pe\u0026ntilde;a E, Leff-Gelman P, Camacho-Arroyo I: Psychological distress, anxiety, depression, stress level, and coping style in HIV-pregnant women in Mexico. \u003cem\u003eBMC psychology \u003c/em\u003e2023, 11(1):366.\u003c/li\u003e\n\u003cli\u003eLazarus RS, Folkman S: Stress, appraisal, and coping.\u003cem\u003e Springer Publishing Company \u003c/em\u003e1984.\u003c/li\u003e\n\u003cli\u003eKiyak S: The relationship of depression, anxiety, and stress with pregnancy symptoms and coping styles in pregnant women: A multi-group structural equation modeling analysis. \u003cem\u003eMidwifery \u003c/em\u003e2024, 136:104103.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"twin pregnancies, depression, anxiety, latent profile, associated factors","lastPublishedDoi":"10.21203/rs.3.rs-8951651/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8951651/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eWhile previous studies have investigated the prevalence and associated factors of prenatal depression and anxiety among women with twin pregnancies, most of these studies have overlooked the substantial variation in symptoms presentation. This study aimed to use latent profile analysis to identify the subgroups and associated factors of prenatal depression and anxiety among women with twin pregnancies.\u003c/p\u003e\u003ch2\u003eMethod\u003c/h2\u003e \u003cp\u003eA cross-sectional study was conducted from October 2024 to October 2025, and a total of 334 women with twin pregnancies were included using convenience sampling. Participants were surveyed using a self-design socio-demographic information, Edinburgh Postnatal Depression Scale, Generalized Anxiety Disorder-7, Perceived Social Support Scale, and Simplified Coping Style Questionnaire. Latent profile analysis was performed to identify prenatal depression and anxiety subgroups among women with twin pregnancies, univariate analysis and multiple logistic regression were used to analyze the related factors.\u003c/p\u003e\u003ch2\u003eResult\u003c/h2\u003e \u003cp\u003eLPA identified two profiles of prenatal depression and anxiety: \u0026ldquo;low-risk group\u0026rdquo; (65.0%) and \u0026ldquo;high-risk group\u0026rdquo; (35.0%). Multivariate logistic regression revealed that lack of medical insurance, pregnancy-related complications, low family support, negative coping styles, and absence of positive coping styles significantly influenced high-risk group (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eTwo subgroups of prenatal depression and anxiety were identified among women with twin pregnancies. In the future, it would be more meaningful for obstetric primary health institutions to establish stratified management system and standardized interventions based on different subgroups.\u003c/p\u003e","manuscriptTitle":"A latent profile analysis of prenatal depression and anxiety in Chinese women with twin pregnancies","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-28 16:30:57","doi":"10.21203/rs.3.rs-8951651/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"23ef3d0c-040f-45fd-bc88-4d4a163607c7","owner":[],"postedDate":"March 28th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-29T08:09:57+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-28 16:30:57","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8951651","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8951651","identity":"rs-8951651","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}